Gesture Input for Users with Motor Impairments on Touchscreens

Ungurean, Ovidiu-Ciprian; Vatavu, Radu-Daniel; Leiva, Luis A.; Plamondon, Réjean

doi:10.1145/3170427.3188619

Cited by 20 publications

(4 citation statements)

References 20 publications

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“…Empirical research indicates that individuals with motor impairments can accurately perform these gestures with devices worn on the wrist, finger, and head, although challenges related to repetition exist [51,52]. Moreover, the performance of stroke gestures for individuals with motor impairments can be enhanced through computer modeling and synthesis [49].…”

Section: Upper-body Gestures Input For People With Motor Impairmentsmentioning

confidence: 99%

Designing Upper-Body Gesture Interaction with and for People with Spinal Muscular Atrophy in VR

Tian,

Wang,

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Fig. 1. Twelve people with Spinal Muscular Atrophy designed upper-body gestures for VR commands. Two of them participated in person, while the other ten joined remotely. All participants actively took part in this research, and Participant 6 preferred to conduct the experiments without turning on the camera.Recent research proposed gaze-assisted gestures to enhance interaction within virtual reality (VR), providing opportunities for people with motor impairments to experience VR. Compared to people with other motor impairments, those with Spinal Muscular Atrophy (SMA) exhibit enhanced distal limb mobility, providing them with more design space. However, it remains unknown what gaze-assisted upper-body gestures people with SMA would want and be able to perform. We conducted an elicitation study in which

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Section: Upper-body Gestures Input For People With Motor Impairmentsmentioning

confidence: 99%

Designing Upper-Body Gesture Interaction with and for People with Spinal Muscular Atrophy in VR

Tian,

Wang,

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…Based on the observation that people with motor impairments rely on their smartphones to overcome other accessibility challenges in the physical world, the extensive research on making mobile devices more accessible [60,66,85,86,86,91], and research on second-screen television watching [15,21], we believe that designing accessible smartphone apps for interacting with television is a feasible alternative to conventional TV remote controls. Without being constrained by the form factor and button layouts of the TV remote control, more accessible designs can be implemented, such as large-area buttons, fewer buttons, and adaptive layouts to match users' motor abilities following the principles of ability-based design [101]; see the SUPPLE system [33] for a relevant example.…”

Section: Smartphone Inputmentioning

confidence: 99%

Coping, Hacking, and DIY: Reframing the Accessibility of Interactions with Television for People with Motor Impairments

Ungurean

Vatavu

2021

ACM International Conference on Interactive Media Experiences

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We conduct an examination of the accessibility challenges experienced by people with upper body motor impairments when interacting with television. We report fndings from a study with N=41 people with motor impairments (spinal cord injury, cerebral palsy, muscular dystrophy) and document their challenges and coping strategies for using the TV remote control, but also their television watching experience and expectations of suitable assistive technology for television. Our results show that, despite several accessible remote control products available on the market, the majority of our participants preferred to DIY and hack, and to adopt coping strategies to be able to use conventional TV remote controls. We contrast their experience against that of a control group with N=41 people without impairments. We refect about the DIY culture and people with motor impairments, and we propose future work directions to increase the accessibility of interactions with television. CCS CONCEPTS• Human-centered computing → Accessibility technologies.

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“…Furthermore, researchers have evaluated the characteristics of stroke gestures synthesized with the ΣΛ model from the perspective of both classification performance [49] and similarity to gesture shapes articulated by real users [50]. Furthermore, it has been shown that synthetic stroke gestures are on par with their human counterparts [47] in terms of articulation speed and geometric characteristics [49,64], and that gesture synthesis is successful for various user groups, such as users with low vision [52] or with motor impairments [94,95].…”

Section: Models Of Human Movement Applied To Gesture Researchmentioning

confidence: 99%

“…Note that other distributions and different noise values may be needed for different user categories, such as gestures articulated by users with visual impairments [52] or by users with motor impairments [95]. We also should note that no perturbations are added to the t 0 parameter in this work, since t 0 is very sensitive even to small fluctuations [23,49].…”

Section: Kinematic Theory Overviewmentioning

confidence: 99%

Omnis Prædictio: Estimating the full spectrum of human performance with stroke gestures

Leiva¹,

Vatavu²,

Martín-Albo³

et al. 2020

International Journal of Human-Computer Studies

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Designing effective, usable, and widely adoptable stroke gesture commands for graphical user interfaces is a challenging task that traditionally involves multiple iterative rounds of prototyping, implementation, and follow-up user studies and controlled experiments for evaluation, verification, and validation. An alternative approach is to employ theoretical models of human performance, which can deliver practitioners with insightful information right from the earliest stages of user interface design. However, very few aspects of the large spectrum of human performance with stroke gesture input have been investigated and modeled so far, leaving researchers and practitioners of gesture-based user interface design with a very narrow range of predictable measures of human performance, mostly focused on estimating production time, of which extremely few cases delivered accompanying software tools to assist modeling. We address this problem by introducing "Omnis Praedictio" (Omnis for short), a generic technique and companion web tool that provides accurate user-independent estimations of any numerical stroke gesture feature, including custom features specified in code. Our experimental results on three public datasets show that our model estimations correlate on average r s > .9 with groundtruth data. Omnis also enables researchers and practitioners to understand human performance with stroke gestures on many levels and, consequently, raises the bar for human performance models and estimation techniques for stroke gesture input.

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Gesture Input for Users with Motor Impairments on Touchscreens

Cited by 20 publications

References 20 publications

Designing Upper-Body Gesture Interaction with and for People with Spinal Muscular Atrophy in VR

Designing Upper-Body Gesture Interaction with and for People with Spinal Muscular Atrophy in VR

Coping, Hacking, and DIY: Reframing the Accessibility of Interactions with Television for People with Motor Impairments

Omnis Prædictio: Estimating the full spectrum of human performance with stroke gestures

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